class_docstr: NAF dataset parser.
  
  The original annotation format of this dataset is stored in json files,
  which has the following keys that will be used here:
      - 'textBBs': List of text bounding box objects
          - 'poly_points': list of [x,y] pairs, the box corners going
              top-left,top-right,bottom-right,bottom-left
          - 'id': id of the textBB, used to match with the text
      - 'transcriptions': Dict of transcription objects, use the 'id' key
          to match with the textBB.
  
  Some special characters are used in the transcription:
  "«text»" indicates that "text" had a strikethrough
  "¿" indicates the transcriber could not read a character
  "§" indicates the whole line or word was illegible
  "" (empty string) is if the field was blank
  
  Args:
      ignore (list(str)): The text of the ignored instances. Default: ['#'].
      det (bool): Whether to parse the detection annotation. Default: True.
          If False, the parser will consider special case in NAF dataset
          where the transcription is not available.
code: def __init__(
      self, ignore: List[str] = ["#"], det: bool = True, **kwargs
  ) -> None:
      self.ignore = ignore
      self.det = det
      super().__init__(**kwargs)
  
file_path: mmocr/mmocr/datasets/preparers/parsers/naf_parser.py
imports: import json
  from typing import List, Tuple
  import numpy
  from mmocr.registry import DATA_PARSERS
  from .base import BaseParser
label_desc: Use image node_id 1 to create a new NAFAnnParser object from inherited base classes: BaseParser with example: obj = NAFAnnParser(ignore, det)